Modeling the Prognostic Impact of Circulating Tumor Cells Enumeration in Metastatic Breast Cancer for Clinical Trial Design Simulation

TY - JOUR

T1 - Modeling the Prognostic Impact of Circulating Tumor Cells Enumeration in Metastatic Breast Cancer for Clinical Trial Design Simulation

AU - Gerratana, Lorenzo

AU - Pierga, Jean-Yves

AU - Reuben, James M

AU - Davis, Andrew A

AU - Wehbe, Firas H

AU - Dirix, Luc

AU - Fehm, Tanja

AU - Nolé, Franco

AU - Gisbert-Criado, Rafael

AU - Mavroudis, Dimitrios

AU - Grisanti, Salvatore

AU - Garcia-Saenz, Jose A

AU - Stebbing, Justin

AU - Caldas, Carlos

AU - Gazzaniga, Paola

AU - Manso, Luis

AU - Zamarchi, Rita

AU - Bonotto, Marta

AU - Fernandez de Lascoiti, Angela

AU - De Mattos-Arruda, Leticia

AU - Ignatiadis, Michail

AU - Sandri, Maria-Teresa

AU - Generali, Daniele

AU - De Angelis, Carmine

AU - Dawson, Sarah-Jane

AU - Janni, Wolfgang

AU - Carañana, Vicente

AU - Riethdorf, Sabine

AU - Solomayer, Erich-Franz

AU - Puglisi, Fabio

AU - Giuliano, Mario

AU - Pantel, Klaus

AU - Bidard, François-Clément

AU - Cristofanilli, Massimo

N1 - © The Author(s) 2022. Published by Oxford University Press.

PY - 2022/7/5

Y1 - 2022/7/5

N2 - Despite the strong prognostic stratification of circulating tumor cells (CTCs) enumeration in metastatic breast cancer (MBC), current clinical trials usually do not include a baseline CTCs in their design. This study aimed to generate a classifier for CTCs prognostic simulation in existing datasets for hypothesis generation in patients with MBC. A K-nearest neighbor machine learning algorithm was trained on a pooled dataset comprising 2436 individual MBC patients from the European Pooled Analysis Consortium and the MD Anderson Cancer Center to identify patients likely to have CTCs ≥ 5/7 mL blood (StageIVaggressive vs StageIVindolent). The model had a 65.1% accuracy and its prognostic impact resulted in a hazard ratio (HR) of 1.89 (Simulatedaggressive vs Simulatedindolent P < .001), similar to patients with actual CTCs enumeration (HR 2.76; P < .001). The classifier's performance was then tested on an independent retrospective database comprising 446 consecutive hormone receptor (HR)-positive HER2-negative MBC patients. The model further stratified clinical subgroups usually considered prognostically homogeneous such as patients with bone-only or liver metastases. Bone-only disease classified as Simulatedaggressive had a significantly worse overall survival (OS; P < .0001), while patients with liver metastases classified as Simulatedindolent had a significantly better prognosis (P < .0001). Consistent results were observed for patients who had undergone CTCs enumeration in the pooled population. The differential prognostic impact of endocrine- (ET) and chemotherapy (CT) was explored across the simulated subgroups. No significant differences were observed between ET and CT in the overall population, both in terms of progression-free survival (PFS) and OS. In contrast, a statistically significant difference, favoring CT over ET was observed among Simulatedaggressive patients (HR: 0.62; P = .030 and HR: 0.60; P = .037, respectively, for PFS and OS).

AB - Despite the strong prognostic stratification of circulating tumor cells (CTCs) enumeration in metastatic breast cancer (MBC), current clinical trials usually do not include a baseline CTCs in their design. This study aimed to generate a classifier for CTCs prognostic simulation in existing datasets for hypothesis generation in patients with MBC. A K-nearest neighbor machine learning algorithm was trained on a pooled dataset comprising 2436 individual MBC patients from the European Pooled Analysis Consortium and the MD Anderson Cancer Center to identify patients likely to have CTCs ≥ 5/7 mL blood (StageIVaggressive vs StageIVindolent). The model had a 65.1% accuracy and its prognostic impact resulted in a hazard ratio (HR) of 1.89 (Simulatedaggressive vs Simulatedindolent P < .001), similar to patients with actual CTCs enumeration (HR 2.76; P < .001). The classifier's performance was then tested on an independent retrospective database comprising 446 consecutive hormone receptor (HR)-positive HER2-negative MBC patients. The model further stratified clinical subgroups usually considered prognostically homogeneous such as patients with bone-only or liver metastases. Bone-only disease classified as Simulatedaggressive had a significantly worse overall survival (OS; P < .0001), while patients with liver metastases classified as Simulatedindolent had a significantly better prognosis (P < .0001). Consistent results were observed for patients who had undergone CTCs enumeration in the pooled population. The differential prognostic impact of endocrine- (ET) and chemotherapy (CT) was explored across the simulated subgroups. No significant differences were observed between ET and CT in the overall population, both in terms of progression-free survival (PFS) and OS. In contrast, a statistically significant difference, favoring CT over ET was observed among Simulatedaggressive patients (HR: 0.62; P = .030 and HR: 0.60; P = .037, respectively, for PFS and OS).

U2 - 10.1093/oncolo/oyac045

DO - 10.1093/oncolo/oyac045

M3 - SCORING: Journal article

C2 - 35278078

VL - 27

SP - e561-e570

JO - ONCOLOGIST

JF - ONCOLOGIST

SN - 1083-7159

IS - 7

ER -